New validation algorithm for data association in SLAM
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Updated: May 11, 2026

Paramagnetic Relaxation Enhancement for Detecting and Characterizing Self-Associations of Intrinsically Disordered Proteins
Published on: September 23, 2021
Edmundo Guerra1, Rodrigo Munguia, Yolanda Bolea
1Automatic Control Department, Technical University of Catalonia, 5 Pau Gargallo St, 08028 Barcelona, Spain. edmundo.guerra@upc.edu
Abstract:
In this work, a novel data validation algorithm for a single-camera SLAM system is introduced. A 6-degree-of-freedom monocular SLAM method based on the delayed inverse-depth (DI-D) feature initialization is used as a benchmark. This SLAM methodology has been improved with the introduction of the proposed data association batch validation technique, the highest order hypothesis compatibility test, HOHCT. This new algorithm is based on the evaluation of statistically compatible hypotheses, and a search algorithm designed to exploit the characteristics of delayed inverse-depth technique. In order to show the capabilities of the proposed technique, experimental tests have been compared with classical methods. The results of the proposed technique outperformed the results of the classical approaches.
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